S.TRUEMAN PhD THESIS 2016

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A theme ‘captures something important about the data in relation to the research question, and represents some level of patterned response or meaning within the data set’ (Braun & Clarke, 2006, p. 82). While a code captures one idea, a theme has a ‘central organizing concept’ (Clarke & Braun, 2013, p. 224) which contains different ideas or aspects related to the concept and ‘tells’ something about the content of the data that is meaningful in relation to the research question (Braun et al., 2013). The researcher re-read the codes to identify patterns by looking for concepts, topics and issues which related to and formed the basis of ‘central organising concepts’; themes (Braun et al., 2013). Some themes were obvious due to salient patterns in the data or consisted of large ‘chunks’ of the data represented in a large code (Charmaz, 2006). The process was revised throughout the analysis stage and refinement resulted in a greater concentration of patterned data around central themes and irrelevant codes being excluded. The themes were visually represented in handwritten matrices, flowcharts, tables, mind maps and thematic maps. The process of making these various visual diagrams aided the researcher to focus his attention on the relationships between themes, and different levels of themes (e.g., main overarching themes and sub-themes within them). The researcher was guided by Braun and Clarke (2006) during the next phase which involved two levels of reviewing and refining the themes. The guiding principle during this phase was assessing the themes against two criteria, internal homogeneity and external heterogeneity (Patton, 1990). ‘Data within themes should cohere together meaningfully, while there should be clear and identifiable distinctions between themes’ (Braun & Clarke, 2006, p. xx). The first stage meant the researcher read all the collated extracts of each theme, and considered whether they formed a coherent pattern. Some of